Self Mapping Organization code tutorial for beginners

i have tried many of posted codes, but i cannot understand well because no comments in the code to describe which step of the SOM it is doing.

as i have a problem understanding when and how do i update the weights of the neighbors.

i made my own code, it depends on linear form not a mesh as following:

%
function [som2]= som_horizontal(x,path)

%x = when it is in the whole hmm prog, is equal the feature matrex generated from all the frames
%path :  in the hmm prog, i used the path to load the weight matrix i
%generated for each gesture when i ran the prog on each gesture for the
%first time, so that i have fixed clustering and be sure it wont change
%with diff random weight generated.
%clc
d=[];
eta=[];
som2=[]
eta(1)=0.5;
dii=0;
x=[1 1 0 0 ;0 0 0 1;1 0 0 0 ;0 0 1 1];%;1 0 0 0 1;0 0 1 1 0]; %feature vectors
N=size(x,2);
m=2;  % number of output nodes, when it is >2 clustering change with each run .
ww = rand(N,m)  %using random weight makes output change between 2 1 2 1  & 1 2 1 2
% using the next weight instead of random , as example says, give the fixed
% output.
%ww=[0.2 0.8;0.6 0.4;0.5 0.7;0.9 0.3];%;0.3 0.5;0.8 0.6]; % waits for each vector and cluster

R=0; %radius is zero , linear

%ww=w.'
wwn=ww;

time=1;
t=1;
k=1;

for iteration=1:100

      for n=1:size(x,1)
          if t<=N
              eta(t)=0.6;
          else
              %eta(t)=0.3;%
              eta(t)=0.5 * eta(k-N); % this is according to the example i have used to apply the code
              % from the following presentation https://genome.tugraz.at/MedicalInformatics2/SOM.pdf
          end

          for j=1:m
              for i=1:N %size(x,2)
                  x(n,i);  %just to read and check the values
                  wwn(i,j);
                  d(i)=((ww(i,j)- x(n,i)).^2); %distance calculation for each weight
                  dii=d(i)+dii;
              end
              di(j)=dii;
              dii=0;
          end

          [v,indx]=min(di);

          for i=1:N %size(x,2)
              ww(i,indx);
              x(n,i);
              %update the weights
              wwn(i,indx)=((1-eta(t))*ww(i,indx))+(eta(t)*x(n,i));
          end
          ww=wwn;
          time=time+1;
          t=t+1;
          somo(n)=indx;
      end

      som2=somo(1,:) ;
      k=k+N;
      iteration;
      eta;
      ww;
  end
  end

[Walter Roberson]

I am not sure if there is a question there, or just example code for the use of interested people?

[John D'Errico]

So, you want a tutorial and explanation of your own code, code written by you?

[eanass abouzeid]

no actualy the question is : i need a toturial code and a good referance to understand the SOM when the output nodes are in mesh topology. with Radius > zero

about the code, this is the code i wrote when the output nodes are not considering neighbors to update their weights. i.e when Radius = zero.